In this article we consider the mathematical foundations and software implementation of the early diagnosis of computer attacks. For this we used the JSM method of automatic hypothesis generation and the theory of case-based models.This software outputs hypotheses about the properties and expected consequences of a new computer attack. The system analyses a set of properties of the computer attack known to the user. For this we use the Base of the cyber attack's precedents, described in the language of fuzzification of Boolean-valued models. Each potential property of the new attack is studied by using the JSM method. This process builds sets of positive and negative hypotheses concerning each property, giving a set of properties and consequences characteristic of the attack that has yet not happened at the time of analysis.The developed algorithm has polynomial complexity.Keywords: information security, computer attack, case of the computer attack, case-based model, fuzzification of the case-based model, JSM-method, JSM-reasoning
The program system of the management of assessment tools for educational process described in the article. The system reduces the time that the teacher spends on the preparation of test materials, allowing you to create a set of assessment documents in a semi-automatic mode. The system implements the ability to create and manage task banks. Each task in the bank has a set of attributes that are involved in the process of generating assessment documents. The system also implements the ability to automatically generate the required number of variants of the assessment documents. At the same time, the algorithm for generating a set of assessment documents works in such a way that, on the one hand, one set includes the most similar variants of assessment documents in structure, and on the other hand, each assessment document in the set is unique. The algorithm for generating a set of assessment documents is based on the clustering algorithm for categorical data. In this paper a modification of the CLOPE algorithm was submitted, which allows you to automatically determine the required number of clusters, depending on the input data. Also, this modification solves the problem of small clusters and the problem of categorical clustering of numerical attributes. The paper also describes an iterative algorithm for the generation of a set of assessment documents.
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